ALSFRS-R decline rate prior to baseline is not useful for stratifying subsequent progression of functional decline.

OBJECTIVE: One of the difficulties in developing a novel drug for patients with amyotrophic lateral sclerosis (ALS) is the significant variation in the clinical course. To control this variation, a 12-week run-in period is used in some clinical trials. Based on the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R) change during the run-in period, only moderate progressors are selected in some clinical trials. Some reports showed that the ALSFRS-R progression rate was associated with survival. However, it is unclear whether the ALSFRS-R change in the run-in period is a useful prognostic factor of the ALSFRS-R change from baseline. In addition, we explore the inclusion criteria that could control the variability in ALS-function progression without setting a run-in period. METHODS: We utilized the Japanese and US ALS registry databases (JaCALS and PRO-ACT). Patients were classified into three populations (rapid, moderate, and slow progressors) based on the ALSFRS-R change prior to baseline. We also classified patients into three prognostic populations based on the ALSFRS-R change from baseline. We confirmed whether each of the three populations were matched with their respective three prognostic populations. RESULTS: Our data showed that the three groups classified by the ALSFRS-R change during the 12 weeks prior to baseline or by the rate of progression from onset to baseline did not accord with the three prognostic groups. CONCLUSIONS: Our results showed that the ALSFRS-R change in the run-in period or from onset to baseline is not useful for stratifying subsequent progression of functional decline in clinical trials.

Efficiency of eSource Direct Data Capture in Investigator-Initiated Clinical Trials in Oncology.

BACKGROUND: Clinical trials have become larger and more complex. Thus, eSource should be used to enhance efficiency. This study aimed to evaluate the impact of the multisite implementation of eSource direct data capture (DDC), which we define as eCRFs for direct data entry in this study, on efficiency by analyzing data from a single investigator-initiated clinical trial in oncology. METHODS: Operational data associated with the targeted study conducted in Japan was used to analyze time from data occurrence to data entry and data finalization, and number of visits to the site and time spent at the site by clinical research associates (CRAs). Additionally, simulations were performed on the change in hours at the clinical sites during the implementation of eSource DDC. RESULTS: No difference in time from data occurrence to data entry was observed between the DDC and the transcribed data fields. However, the DDC fields could be finalized 4 days earlier than the non-DDC fields. Additionally, although no difference was observed in the number of visits for source data verification (SDV) by CRAs, a comparison among sites that introduced eSource DDC and those that did not showed that the time spent at the site for SDV was reduced. Furthermore, the simulation results indicated that even a small amount of data to be collected or a small percentage of DDC-capable items may lead to greater efficiency when the number of subjects per site is significant. CONCLUSIONS: The implementation of eSource DDC may enhance efficiency depending on the study framework and type and number of items to be collected.

Evaluation of Data Errors and Monitoring Activities in a Trial in Japan Using a Risk-Based Approach Including Central Monitoring and Site Risk Assessment.

BACKGROUND: Risk-based monitoring (RBM) is a slow uptake in some trial sponsors. There are three main reasons for this. First, there is the fear of making large investments into advanced RBM technology solutions. Second, it is considered that RBM is most suitable for large, complex trials. Third, there is the fear of errors in both critical and non-critical data, appearing as reduced on-site monitoring is being conducted. METHODS: Our RBM team identified, evaluated, and mitigated trial risks, as well as devised a monitoring strategy. The clinical research associate (CRA) assessed the site risks, and the RBM team conducted central monitoring. We compared all data errors and on-site monitoring time between the partial switching sites [sites that had switched to partial source data verification (SDV) and source data review (SDR)] and the 100% SDV and SDR sites (sites that had implemented 100% SDV and SDR). RESULTS: Partial switching sites did not require any critical data correction and had a smaller number of data corrections through on-site monitoring than the 100% SDV and SDR sites. The RBM strategy reduced the on-site monitoring time by 30%. CONCLUSIONS: The results suggest that RBM can be successfully implemented through the use of site risk assessment and central monitoring with practically no additional investment in technology and still produced similar results in terms of subject safety and data quality, as well as the cost savings that have been reported in global complex studies.

Cluster analysis of pharmacists' work attitudes.

Background: Few studies in Japan use clustering to examine the work attitudes of pharmacists. This study conducts an exploratory analysis to classify those attitudes based on previous studies to help staff pharmacists and their management to understand their mutually beneficial requirements. Methods: Survey data collected in previous studies from 1 228 community pharmacists and 419 hospital pharmacists were analyzed using Quantification Theory 3 and clustering. Results: Among community pharmacists, two clusters, namely 30- to 34-year-old married males and married males aged over 35 years, reported the highest job satisfaction, intending to remain in their jobs for 5 years or more or until retirement. Conversely, one cluster of 35- to 39-year-old single females reported the lowest job satisfaction and intended to remain for less than 5  years or were undecided. Among hospital pharmacists, one cluster of 22- to 25-year-old single males reported the highest job satisfaction and intended to remain for more than 5 years. Conversely, one cluster of 30- to 34-year-old married males reported the lowest job satisfaction and a period of working undetermined. Conclusions: This study used clustering to explore how pharmacists of different ages, marital statuses, and experience felt regarding their work. Job satisfaction and human relationships are significant in considering future work plans of practicing pharmacists. Pharmacy staff, supervisors, and managers of community or hospital pharmacies must recognize features of pharmacists' work attitudes for offering high-quality service to patients.

Streptomyces hokutonensis sp. nov., a novel actinomycete isolated from the strawberry root rhizosphere.

A polyphasic approach was used to determine the taxonomic position of actinomycete strain R1-NS-10(T), which was isolated from a sample of strawberry root rhizosphere obtained from Hokuto, Yamanashi, Japan. Strain R1-NS-10(T) was Gram-staining-positive and aerobic, and formed brownish-white aerial mycelia and grayish-brown substrate mycelia on ISP-2 medium. The strain grew in the presence of 0-5% (w/v) NaCl and optimally grew without NaCl. The strain grew at pH 5-8, and the optimum for growth was pH 7. The optimal growth temperature was 30 °C, but the strain grew at 5-37 °C. Whole-cell hydrolysates of strain R1-NS-10(T) contained A2pm, galactose, mannose and rhamnose. The predominant menaquinones were MK-9(H6) and MK-9(H8). The major cellular fatty acids were anteiso-C15:0 and iso-C16:0. Comparative 16S rRNA gene sequence analysis revealed that strain R1-NS-10(T) was most closely related to Streptomyces prunicolor NBRC 13075(T) (99.4%). The draft genome sequences of both strains were determined for characterization of genome sequence-related parameters such as average nucleotide identity (ANI) and the diversity of secondary metabolite biosynthetic gene clusters. DNA-DNA hybridization (DDH) and ANI values for both strains were below the species delineation cutoff, and differences in physiological and biochemical characteristics differentiated strain R1-NS-10(T) from its closest phylogenetic relative. On the basis of these data, we propose that strain R1-NS-10(T) (=NBRC 108812(T)=KCTC 29186(T)) should be classified as the type strain of a novel Streptomyces species named Streptomyces hokutonensis sp. nov.